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Pop-out in visual search of moving targets in the archer fish

Author

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  • Mor Ben-Tov

    (Ben-Gurion University of the Negev
    Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev)

  • Opher Donchin

    (Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev
    Ben-Gurion University of the Negev
    Erasmus MC)

  • Ohad Ben-Shahar

    (Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev
    Ben-Gurion University of the Negev)

  • Ronen Segev

    (Ben-Gurion University of the Negev
    Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev)

Abstract

Pop-out in visual search reflects the capacity of observers to rapidly detect visual targets independent of the number of distracting objects in the background. Although it may be beneficial to most animals, pop-out behaviour has been observed only in mammals, where neural correlates are found in primary visual cortex as contextually modulated neurons that encode aspects of saliency. Here we show that archer fish can also utilize this important search mechanism by exhibiting pop-out of moving targets. We explore neural correlates of this behaviour and report the presence of contextually modulated neurons in the optic tectum that may constitute the neural substrate for a saliency map. Furthermore, we find that both behaving fish and neural responses exhibit additive responses to multiple visual features. These findings suggest that similar neural computations underlie pop-out behaviour in mammals and fish, and that pop-out may be a universal search mechanism across all vertebrates.

Suggested Citation

  • Mor Ben-Tov & Opher Donchin & Ohad Ben-Shahar & Ronen Segev, 2015. "Pop-out in visual search of moving targets in the archer fish," Nature Communications, Nature, vol. 6(1), pages 1-11, May.
  • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms7476
    DOI: 10.1038/ncomms7476
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    Cited by:

    1. Li Zhaoping & Li Zhe, 2015. "Primary Visual Cortex as a Saliency Map: A Parameter-Free Prediction and Its Test by Behavioral Data," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-39, October.

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